The effects of neurofeedback training on the spectral topography of the electroencephalogram.

Journal Article (Clinical Trial;Journal Article)


To investigate the impact of EEG frequency band biofeedback (neurofeedback) training on spectral EEG topography, which is presumed to mediate cognitive-behavioural training effects. In order to assess the effect of commonly applied neurofeedback protocols on spectral EEG composition, two studies involving healthy participants were carried out.


In Experiment 1, subjects were trained on low beta (12-15 Hz), beta1 (15-18 Hz), and alpha/theta (8-11 Hz/5-8 Hz) protocols, with spectral resting EEG assessed before and after training. The specific associations between learning indices of each individual training protocol and changes in absolute and relative spectral EEG topography was assessed by means of partial correlation analyses. Results of Experiment 1 served to generate hypotheses for Experiment 2, where subjects were randomly allocated to independent groups of low beta, beta1, and alpha/theta training. Spectral resting EEG measures were contrasted prior and subsequent to training within each group.


Only few associations between particular protocols and spectral EEG changes were found to be consistent across the two studies, and these did not correspond to expectations based on the operant contingencies trained. Low-beta training was found to be somewhat associated with reduced post-training low-beta activity, while more reliably, alpha/theta training was associated with reduced relative frontal beta band activity.


The results document that neurofeedback training of frequency components does affect spectral EEG topography in healthy subjects, but that these effects do not necessarily correspond to either the frequencies or the scalp locations addressed by the training contingencies. The association between alpha/theta training and replicable reductions in frontal beta activity constitutes novel empirical neurophysiological evidence supporting inter alia the training's purported role in reducing agitation and anxiety.


These results underline the complexity of the neural dynamics involved EEG self-regulation and emphasize the need for empirical validation of predictable neurophysiological outcomes of training EEG biofeedback protocols.

Full Text

Duke Authors

Cited Authors

  • Egner, T; Zech, TF; Gruzelier, JH

Published Date

  • November 2004

Published In

Volume / Issue

  • 115 / 11

Start / End Page

  • 2452 - 2460

PubMed ID

  • 15465432

Pubmed Central ID

  • 15465432

Electronic International Standard Serial Number (EISSN)

  • 1872-8952

International Standard Serial Number (ISSN)

  • 1388-2457

Digital Object Identifier (DOI)

  • 10.1016/j.clinph.2004.05.033


  • eng